CN114559960A - Collision early warning system based on fusion of forward-looking camera and rear millimeter wave radar - Google Patents
Collision early warning system based on fusion of forward-looking camera and rear millimeter wave radar Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0015—Planning or execution of driving tasks specially adapted for safety
- B60W60/0016—Planning or execution of driving tasks specially adapted for safety of the vehicle or its occupants
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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Abstract
The invention relates to the technical field of automatic driving of intelligent vehicles, and discloses a collision early warning system based on fusion of a front-view camera and a rear millimeter wave radar, which comprises a visual detection module, a front-view radar module and a rear-view radar module, wherein the visual detection module is used for shooting and processing road condition images in front of an intelligent vehicle to obtain front road condition information; the rear millimeter wave radar is used for enabling a user to obtain rear obstacle information of the intelligent vehicle, wherein the rear obstacle information comprises obstacle speed; the data processing module is used for processing the road condition information and the rear obstacle information and comprises a rear early warning processing unit, wherein the rear early warning processing unit is used for obtaining collision time according to the relative speed of the rear obstacle and the intelligent vehicle in the y direction and giving an alarm when the collision time reaches a rear collision threshold value. The early warning function has guaranteed intelligent vehicle's safe traveling around this scheme, greatly reduced the probability that the vehicle bumps, improve intelligent vehicle's security of traveling.
Description
Technical Field
The invention relates to the technical field of automatic driving of intelligent vehicles, in particular to a collision early warning system based on fusion of a front-view camera and a rear millimeter wave radar.
Background
In recent years, artificial intelligence technology is applied in the automobile industry, automobiles are continuously developed towards intellectualization, and a plurality of vehicles are provided with certain driving auxiliary devices and intelligent devices to assist drivers to sense and control the vehicles, so that the safety during driving can be further improved. When the front and rear vehicles run, the intelligent vehicle can avoid the front vehicle from rear-end collision through an automatic emergency braking technology in the vehicle-mounted driving auxiliary device, but when the intelligent vehicle is rear-end collision by the rear vehicle, active danger avoidance cannot be carried out. Or when the automatic driving vehicle is at a traffic light such as a crossroad, the stopping posture of the self vehicle is not correct, or the stopping position is a lane waiting for turning, the vehicle body is stopped at a certain angle, and due to the fact that the self vehicle is static, when a target passes through the lane beside, the warning and the false alarm of the rear collision are caused due to the fact that the angle exists in the parking of the self vehicle.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a collision early warning system based on fusion of a forward-looking camera and a rear millimeter wave radar.
In order to achieve the above purpose, the invention provides the following technical scheme:
a collision early warning system based on fusion of a forward-looking camera and a rear millimeter wave radar,
the visual detection module is used for shooting and processing road condition images in front of the intelligent vehicle to obtain front road condition information;
the rear millimeter wave radar is used for enabling a user to obtain rear obstacle information of the intelligent vehicle, wherein the rear obstacle information comprises obstacle speed;
the data processing module is used for processing the road condition information and the rear obstacle information and comprises a rear early warning processing unit, the rear early warning processing unit is used for obtaining collision time according to the relative speed of the rear obstacle and the intelligent vehicle in the y direction, and alarming when the collision time reaches a rear collision threshold value, wherein the calculation formula of the trigger time is as follows:
wherein t is trigger time, VrThe relative speed of the rear obstacle and the intelligent vehicle in the y direction.
In the invention, further, the method for acquiring the relative speed of the rear obstacle and the intelligent vehicle in the y direction is vr＝(v1-v2) And tan theta, wherein V1 is the speed of the obstacle, V2 is the speed of the intelligent vehicle, and the heading angle of the intelligent vehicle is shown.
In the present invention, further, the method for obtaining the relative heading angle includes: and determining a lane reference line of the intelligent vehicle, and constructing a right triangle to obtain a relative course angle by pre-aiming two points in front of the intelligent vehicle.
In the present invention, the vision detecting module at least includes a front-view camera, and the front-view camera is used for shooting a front road condition image.
In the invention, the data processing module further comprises a front early warning unit, and the front early warning unit is used for processing the image acquired by the forward-looking camera to obtain a lane reference line and acquiring front obstacle information.
In the invention, further, the processing of the image acquired by the front-view camera includes reading the image, preprocessing the image, extracting image features to obtain a lane reference line, acquiring the transverse position of the intelligent vehicle in a lane line fitting manner, and triggering a lane departure alarm signal when the transverse position of the intelligent vehicle is smaller than a preset departure threshold value.
In the invention, further, the collected front obstacle information comprises the speed of the front obstacle and the distance between the front obstacle, and when the speed difference between the intelligent vehicle and the front obstacle is greater than a set speed threshold value and the distance difference between the intelligent vehicle and the front obstacle is greater than a distance threshold value, an early warning signal is triggered to start.
In the present invention, further, the method for obtaining the lane reference line is: selecting a distance along the heading angle direction of the vehicle head, uniformly sampling according to a certain distance in the distance, solving a first derivative and a second derivative of a polynomial function fitted to a reference line to calculate a curvature value of a uniform sampling point, carrying out statistical analysis on curvature values of a plurality of sampling points, calculating a maximum value, a minimum value, a mean value and a variance, constructing an algorithm model to solve a weighted curvature value, and representing a lane reference line through the weighted curvature.
In the present invention, further, the obtaining of the lateral position of the intelligent vehicle by the lane line fitting manner includes marking a change rate of the relative position of the intelligent vehicle by the relative change amounts of the vehicle offset and the heading angle in the two frames of images:
wherein the content of the first and second substances,
the rate of change of the heading angle is indicated,
the change rate of the heading angle, delta c is the change amount of the offset of the intelligent vehicle of two adjacent frames of images, delta t is the interval time of the two frames of images, and delta theta is the change amount of the heading angle in the two frames of images.
In the invention, further, the motion of the intelligent vehicle adopts a transverse feedback control strategy.
Compared with the prior art, the invention has the beneficial effects that:
the device detects front and rear obstacles by fusing the front-view camera and the rear millimeter wave radar, obtains collision time according to the relative speed of the rear obstacle and the intelligent vehicle in the y direction, and gives an alarm when the collision time reaches a rear collision threshold value, so that the potential safety hazard of collision caused by the fact that a target passes through a side lane and the vehicle is parked at a certain angle under the conditions that the self-vehicle stops in an incorrect stopping posture or the stopping position is a lane waiting for turning when the intelligent vehicle is at traffic lights such as a crossroad and the like, and the vehicle body is parked at the certain angle is solved. Simultaneously, this scheme still fuses the place ahead early warning unit, realizes the skew early warning of lane line in intelligent vehicle the place ahead to and when waiting the red light, the place ahead vehicle has rolled out, and when intelligent vehicle did not start in the time of predetermineeing, will trigger and start early warning signal. Therefore, the safe driving of the intelligent vehicle is ensured, the collision probability of the vehicle is greatly reduced, and the driving safety of the intelligent vehicle is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is an overall structure diagram of a collision early warning system based on fusion of a front-view camera and a rear millimeter wave radar according to the present invention;
FIG. 2 is an overall structure diagram of a collision early warning system based on fusion of a front-view camera and a rear millimeter wave radar according to the present invention;
FIG. 3 is a diagram of a collision warning system based on fusion of a front-view camera and a rear millimeter wave radar in accordance with the present invention;
fig. 4 is a diagram of a collision warning system based on fusion of a front-view camera and a rear millimeter wave radar according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When a component is referred to as being "connected" to another component, it can be directly connected to the other component or intervening components may also be present. When a component is referred to as being "disposed on" another component, it can be directly on the other component or intervening components may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for purposes of illustration only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Referring to fig. 1 and 2, a preferred embodiment of the present invention provides a collision warning system based on a front-view camera and a rear millimeter-wave radar, which includes
The visual detection module is used for shooting and processing road condition images in front of the intelligent vehicle to obtain front road condition information;
the rear millimeter wave radar is used for enabling a user to obtain rear obstacle information of the intelligent vehicle, wherein the rear obstacle information comprises obstacle speed;
the data processing module is used for processing the road condition information and the rear obstacle information and comprises a rear early warning processing unit, the rear early warning processing unit is used for obtaining collision time according to the relative speed of the rear obstacle and the intelligent vehicle in the y direction, and alarming when the collision time reaches a rear collision threshold value, wherein the calculation formula of the trigger time is as follows:
where t is the trigger time, VrThe relative speed of the rear obstacle and the intelligent vehicle in the y direction.
Specifically, a plurality of rear millimeter wave radars can be arranged and are mainly used for detecting the motion states of rear obstacles, including the speed, the distance and the like of the vehicle, and by utilizing the characteristics of the rear millimeter wave radars, the system is provided with a rear early warning processing unit, so that the problem that when the vehicle is at a traffic light such as a crossroad and the like, the vehicle stops at an incorrect posture, or the stopping position is a lane waiting for turning, the vehicle body stops at a certain angle, when a target runs through a side lane due to the static state of the vehicle, and the relative speed of the target vehicle and the vehicle has a certain component in the y direction of the vehicle due to the angle of the parking of the vehicle, thereby causing the potential safety hazard of collision.
For this reason, the scheme obtains the collision time according to the relative speed of the rear barrier and the intelligent vehicle in the y direction, and the alarm is given when the collision time reaches the rear collision threshold value, wherein the rear collision threshold value is set to be 1.4 s. V is the relative speed of the rear obstacle and the intelligent vehicle in the y directionr＝(v1-v2) tan theta, where V1 is the obstacle vehicle speed, V2 is the smart vehicle speed, and theta is the relative heading angle of the smart vehicle.
In the invention, further, the method for obtaining the relative course angle comprises the following steps: and determining a lane reference line of the intelligent vehicle, and constructing a right triangle to obtain a relative course angle by pre-aiming two points in front of the intelligent vehicle.
Specifically, as shown in fig. 4, the vertical distances from the heading angle (dotted line) direction at X0 and X2 to the heading angle (dotted line) direction of the distance calculation reference lines at the distances X0 and X2 in the heading angle direction are selected to be D0 and D2, and a right triangle is constructed, so that the relative heading angle is calculated to be θ.
Based on the above example, in the present embodiment, as shown in fig. 3, the motion of the smart vehicle employs a lateral feedback control strategy. Specifically, a transverse controller which is composed of a feedforward controller and a feedback controller and can simulate human driving behaviors is designed aiming at the characteristics that an intelligent vehicle has high nonlinear dynamic characteristics, uncertainty of parameters and the like. In order to improve the control precision and eliminate the steady-state error, a transverse feedback control strategy is provided, a visual detection module determines the relative position and the posture of the intelligent vehicle and a reference line, and the actual angle output is compensated through a feedback controller. The feedforward and feedback controllers of the transverse controller compensate the actual steering wheel corner of the vehicle to quickly, smoothly and stably follow the expected steering wheel corner, control the vehicle to run along a planned path, and ensure the running safety, stability and riding comfort of the vehicle. When the intelligent vehicle based on visual navigation runs, the feedforward controller calculates the relative course angle, calculates the transverse deviation, calculates the preview curvature, the longitudinal speed and other feedforward information through the front preview point, and constructs an algorithm model to calculate the expected turning angle of a steering wheel through a machine learning means according to certain strategies and modes, such as regression analysis, a neural network and a principal component analysis mode, so as to control the vehicle to run along a specified path.
In the present invention, the vision detecting module at least includes a front-view camera, and the front-view camera is used for shooting a front road condition image. The data processing module further comprises a front early warning unit, and the front early warning unit is used for processing the images acquired by the front-view camera to obtain a lane reference line and acquiring front obstacle information.
Specifically, the processing of the image acquired by the forward-looking camera includes reading the image, preprocessing the image, and extracting image features to obtain a lane reference line.
Based on the above embodiment, the preprocessing the image includes:
carrying out gray level conversion on the acquired image, and specifically carrying out gray level calculation by a weighted average calculation method;
and carrying out image enhancement in the spatial region to improve the image definition. Specifically, the image may be enhanced by mean filtering or frequency filtering.
Therefore, through the image processing, the noise is prevented from being generated in the image due to the influence of factors such as light and environment during photographing, so that a clear image is obtained, and subsequent lane recognition is facilitated.
In the present invention, further, the method for obtaining the lane reference line is: selecting a distance along the heading angle direction of the vehicle head, uniformly sampling according to a certain distance in the distance, solving a first derivative and a second derivative of a polynomial function fitted to a reference line to calculate a curvature value of a uniform sampling point, carrying out statistical analysis on curvature values of a plurality of sampling points, calculating a maximum value, a minimum value, a mean value and a variance, constructing an algorithm model to solve a weighted curvature value, and representing a lane reference line through the weighted curvature.
Based on the embodiment, as shown in fig. 4, a distance X3 in the heading angle direction is selected, uniform sampling is performed according to a certain distance from 0 to the distance X3, a first derivative and a second derivative are solved for a polynomial function fitted to a reference line, curvature values of uniform sampling points are calculated, then statistical analysis is performed on the curvature values of a plurality of sampling points, a maximum value, a minimum value, a mean value and a variance are calculated, an algorithm model is constructed, a weighted curvature value is solved, whether the reference line is a left curve or a right curve or a straight road is represented by the weighted curvature, and the radius of the curve is large.
In the invention, further, in the scheme, the transverse position of the intelligent vehicle is obtained in a lane line fitting mode, and when the transverse position of the intelligent vehicle is smaller than a preset deviation threshold value, a lane deviation alarm signal is triggered. The lane fitting method is mainly used for determining the posture and the position of the vehicle.
Specifically, the acquiring of the lateral position of the intelligent vehicle by the lane line fitting mode includes marking a change rate of the relative position of the intelligent vehicle by the relative change amounts of the vehicle offset and the course angle in the two frames of images:
wherein the content of the first and second substances,
the rate of change of the heading angle is indicated,
the change rate of the course angle, delta c is the change amount of the offset of the intelligent vehicle of two adjacent frame images, delta t is the interval time of the two frame images, and delta theta is the change amount of the course angle in the two frame images.
By continuously processing each frame of image, real-time acquisition is realized
The motion deviation and the change rate of the vehicle only can be obtained to determine the position of the intelligent vehicle, so that the dynamic analysis of the vehicle only can be facilitated.
And after the position of the vehicle in the lane is determined, the distance between the intelligent vehicle and the left and right reference lines can be determined, when the distance between the intelligent vehicle and the reference lines is smaller than a preset deviation threshold value, lane deviation early warning is carried out, wherein the intelligent vehicle is pressed when the deviation threshold value is set to be 0.
In the invention, further, when waiting for the red light, the front vehicle already drives out, and the intelligent vehicle may not be started due to the driver himself or the like, so that the rear vehicle is crowded, the light passing time is insufficient, and the like. In order to solve the technical scheme, the collected front obstacle information comprises the speed of the front obstacle and the distance between the front obstacle, and when the speed difference between the intelligent vehicle and the front obstacle is larger than a set speed threshold value and the distance difference between the intelligent vehicle and the front obstacle is larger than a distance threshold value, an early warning signal is triggered and started. That is, when the vehicle waits for a traffic light, most vehicles are in a stationary state, and the speed of the vehicle at the beginning of starting or departure is not too high, so after the front vehicle has traveled a certain distance, if the intelligent vehicle is still in a relatively stationary state at this time, the speed difference between the two is increased, and at this time, a start warning is given. Through two judgments of speed and distance, the misjudgment probability can be effectively reduced.
So, this scheme still fuses the place ahead early warning unit, realizes the lane line skew early warning in intelligent vehicle the place ahead to and. Therefore, the safe driving of the intelligent vehicle is ensured, the probability of vehicle collision is greatly reduced, and the driving safety of the intelligent vehicle is improved.
It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the protection scope of the claims of the present invention.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
It should be understood that the technical problems can be solved by combining and combining the features of the embodiments from the claims.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part thereof which substantially contributes to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is intended to describe in detail the preferred embodiments of the present invention, but the embodiments are not intended to limit the scope of the claims of the present invention, and all equivalent changes and modifications made within the technical spirit of the present invention should fall within the scope of the claims of the present invention.
Claims (10)
1. A collision early warning system based on fusion of a forward-looking camera and a rear millimeter wave radar is characterized by comprising
The visual detection module is used for shooting and processing road condition images in front of the intelligent vehicle to obtain front road condition information;
the rear millimeter wave radar is used for enabling a user to obtain rear obstacle information of the intelligent vehicle, wherein the rear obstacle information comprises obstacle speed;
the data processing module is used for processing the road condition information and the rear obstacle information and comprises a rear early warning processing unit, the rear early warning processing unit is used for obtaining collision time according to the relative speed of the rear obstacle and the intelligent vehicle in the y direction, and alarming when the collision time reaches a rear collision threshold value, wherein the calculation formula of the trigger time is as follows:
where t is the trigger time, VrThe relative speed of the rear obstacle and the intelligent vehicle in the y direction.
2. The system of claim 1, wherein the relative speed V of the rear barrier and the intelligent vehicle in the y direction is a relative speed of the rear barrier and the intelligent vehicle in the y directionrIs obtained by the method vr＝(v1-v2) And tan theta, wherein V1 is the speed of the obstacle, V2 is the speed of the intelligent vehicle, and theta is the heading angle of the intelligent vehicle.
3. The system of claim 1, wherein the method for obtaining the relative course angle comprises: and determining a lane reference line of the intelligent vehicle, and constructing a right triangle to obtain a relative course angle by pre-aiming two points in front of the intelligent vehicle.
4. The collision early warning system based on the fusion of the front-view camera and the rear millimeter wave radar as claimed in claim 1, wherein the vision detection module at least comprises a front-view camera for capturing images of road conditions ahead.
5. The collision early warning system based on the fusion of the front-view camera and the rear millimeter wave radar as claimed in claim 4, wherein the data processing module further comprises a front early warning unit, and the front early warning unit is used for processing the image acquired by the front-view camera to obtain a lane reference line and acquiring front obstacle information.
6. The collision early warning system based on fusion of the front-view camera and the rear millimeter wave radar as claimed in claim 5, wherein the processing of the image obtained by the front-view camera comprises reading the image, preprocessing the image, extracting image features to obtain a lane reference line, obtaining the transverse position of the intelligent vehicle in a lane line fitting manner, and triggering a lane departure warning signal when the transverse position of the intelligent vehicle is smaller than a preset departure threshold.
7. The collision early warning system based on the fusion of the front-view camera and the rear millimeter wave radar as claimed in claim 5, wherein the collected front obstacle information includes a front obstacle speed and a front obstacle distance, and when a speed difference between the intelligent vehicle and the front obstacle is greater than a set speed threshold and a distance difference between two sides of the intelligent vehicle is greater than a distance threshold, the early warning signal is triggered to be started.
8. The system of claim 6, wherein the method for obtaining the lane reference line comprises the following steps: selecting a distance along the heading angle direction of the vehicle head, uniformly sampling according to a certain distance in the distance, solving a first derivative and a second derivative of a polynomial function fitted to a reference line to calculate a curvature value of a uniform sampling point, carrying out statistical analysis on curvature values of a plurality of sampling points, calculating a maximum value, a minimum value, a mean value and a variance, constructing an algorithm model to solve a weighted curvature value, and representing a lane reference line through the weighted curvature.
9. The collision early warning system based on fusion of the forward-looking camera and the rear millimeter wave radar as claimed in claim 5, wherein the obtaining of the lateral position of the intelligent vehicle by means of lane line fitting includes marking a change rate of the relative position of the intelligent vehicle by the relative change amount of the vehicle offset and the course angle in the two frames of images:
wherein the content of the first and second substances,
the rate of change of the heading angle is indicated,
the change rate of the heading angle, delta c is the change amount of the offset of the intelligent vehicle of two adjacent frames of images, delta t is the interval time of the two frames of images, and delta theta is the change amount of the heading angle in the two frames of images.
10. The system of claim 1, wherein a transverse feedback control strategy is adopted for movement of the intelligent vehicle.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210307178.5A CN114559960A (en) | 2022-03-25 | 2022-03-25 | Collision early warning system based on fusion of forward-looking camera and rear millimeter wave radar |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210307178.5A CN114559960A (en) | 2022-03-25 | 2022-03-25 | Collision early warning system based on fusion of forward-looking camera and rear millimeter wave radar |
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| CN114559960A true CN114559960A (en) | 2022-05-31 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115366940A (en) * | 2022-08-29 | 2022-11-22 | 中南大学 | Train with self-adaptive crashworthiness protection device |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115366940A (en) * | 2022-08-29 | 2022-11-22 | 中南大学 | Train with self-adaptive crashworthiness protection device |
| CN115366940B (en) * | 2022-08-29 | 2023-09-26 | 中南大学 | Train with self-adaptive crashworthiness protection device |
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